While insurance companies pioneered the use of predictive analytics for pricing and risk management, they’ve fallen short when it comes to using those same tools in other places. Notable gaps include:
- Aggregating customer information.
- Tailoring products, prices and channels to specific customers.
- Understanding outcomes of specific business processes.
What are the five steps that will make or break your analytics strategy?
Here are five basic steps to begin building a robust analytics strategy.
- Understand your data. Insurers need high-quality internal data, as well as external data. Many insurers can benefit from adopting an enterprise-level data sourcing approach and a standardized insurance data model.
- Focus on business problems, not technology. Remember, technology is an enabler for business needs. It’s important to use analytics to incorporate business insights back into business processes.
- Select appropriate technology. Rather than bells and whistles, focus on the functionality that’s essential to achieving your business goals.
- Take an enterprise approach to analytics. This means creating a formal enterprise analytics organization, staffed with professionals who have the right skills. Eliminate analytics silos, which prevent your ability to look across the enterprise to see the big picture.
- Consider the intelligent use of outsourcing. Outsourcing can help insurers reduce costs and gain access to a stable, scalable pool of talent. It’s important to select vendors that align with business strategy and that have deep expertise in the insurance business process.
To learn more, download The Path to High Performance in Insurance: Transforming Distribution and Marketing with Predictive Analytics (pdf; opens in a new window).